Unveiling the Unexpected: Why Doctors Should Look beyond the Lungs when Predicting COVID-19 Mortality.

Introduction: The main objective of this study was to identify the best combination of admission day parameters for predicting COVID-19 mortality in hospitalized patients. Furthermore, we sought to compare the predictive capacity of pulmonary parameters to that of renal parameters for mortality from COVID-19.

Methods: In this retrospective study, all patients admitted to a tertiary hospital between September 1st, 2020, and December 31st, 2020, who were clinically symptomatic and tested positive for COVID-19, were included.

The searching for agents for Alzheimer's disease treatment via the system of self-consistent models.

Robust quantitative structure-activity relationships (QSARs) for hBACE-1 inhibitors (pIC50) for a large database ( = 1706) are established. New statistical criteria of the predictive potential of models are suggested and tested. These criteria are the index of ideality of correlation () and the correlation intensity index ().

The sequence of amino acids as the basis for the model of biological activity of peptides.

The algorithm of building up a model for the biological activity of peptides as a mathematical function of a sequence of amino acids is suggested. The general scheme is the following: The total set of available data is distributed into the active training set, passive training set, calibration set, and validation set. The training (both active and passive) and calibration sets are a system of generation of a model of biological activity where each amino acid obtains special correlation weight.

The study of the index of ideality of correlation as a new criterion of predictive potential of QSPR/QSAR-models.

Acetylcholinesterase (AChE) inhibitors, dihydrofolate reductase inhibitors (DHFR), Toxicity in Tetrahymena pyriformis (TP), Acute Toxicity in fathead minnow (TFat), Water solubility (WS), and Acute Aquatic Toxicity in Daphnia magna (DM) are examined as endpoints to establish quantitative structure - property/activity relationships (QSPRs/QSARs). The Index of Ideality of Correlation (IIC) is a measure of predictive potential. The IIC has been studied in a few recent works.

Prevalence and Risk Factors of Osteoporosis in Postmenopausal Women with Type 2 Diabetes Mellitus.

Objective: Patients with type 2 diabetes (T2DM) are at increased risk of fractures. The aim of this study is to analyze the prevalence and risk factors of osteoporosis and osteoporosis related fractures in postmenopausal women with T2DM.

Methods: A total of 112 postmenopausal women with T2DM and 171 control nondiabetic women received a standardized questionnaire on osteoporosis risk factors, and were evaluated for bone mineral density (BMD, by using a dual energy X-ray absorptiometry), biochemical markers of bone and glucose metabolism, soluble receptor for advanced glycation end products (sRAGE) and its gene polymorphisms (rs1800625 or rs2070600).

CORAL Software: Analysis of Impacts of Pharmaceutical Agents Upon Metabolism via the Optimal Descriptors.

Backgrounds: The CORAL software has been developed as a tool to build up quantitative structure- activity relationships (QSAR) for various endpoints.

Objective: The task of the present work was to estimate and to compare QSAR models for biochemical activity of various therapeutic agents, which are built up by the CORAL software.

Method: The Monte Carlo technique gives possibility to build up predictive model of an endpoint by means of selection of so-called correlation weights of various molecular features extracted from simplified molecular input-line entry system (SMILES).

Improved building up a model of toxicity towards Pimephales promelas by the Monte Carlo method.

By optimization of so-called correlation weights of attributes of simplified molecular input-line entry system (SMILES) quantitative structure - activity relationships (QSAR) for toxicity towards Pimephales promelas are established. A new SMILES attribute has been utilized in this work. This attribute is a molecular descriptor, which reflects (i) presence of different kinds of bonds (double, triple, and stereo chemical bonds); (ii) presence of nitrogen, oxygen, sulphur, and phosphorus atoms; and (iii) presence of fluorine, chlorine, bromine, and iodine atoms.

The Utilization of the Monte Carlo Technique for Rational Drug Discovery.

Quantitative structure - activity relationships (QSARs) are built up for three endpoints (i) blood-brain barrier permeability; (ii) butyrylcholinesterase (BChE) inhibitory activity; and (iii) for biological effect of antibacterial drugs. The models are based on utilization of the Monte Carlo technique. The CORAL software available on the Internet has been utilized for the calculations.

High Prevalence of Hypovitaminosis D in Postmenopausal Women with Type 2 Diabetes Mellitus.

The link between vitamin D and type 2 diabetes mellitus (T2DM) is intensively studied. This study aims to define the serum concentration of 25-hydroxyvitamin D (25-OH D) and to investigate the relationship between 25-OH D status, glycated hemoglobin (HbA1c) and body composition in postmenopausal women with T2DM and in non-diabetic controls. In this cross-sectional study, 75 women with T2DM and 32 control subjects were selected.

Searching therapeutic agents for treatment of Alzheimer disease using the Monte Carlo method.

Quantitative structure - activity relationships (QSARs) for the pIC50 (binding affinity) of gamma-secretase inhibitors can be constructed with the Monte Carlo method using CORAL software (http://www.insilico.eu/coral).